Results 121 to 130 of about 43,164 (298)

Harnessing Phase Dynamics Across Diverse Frequencies with Multifrequency Oscillatory Neural Networks

Advanced Intelligent Discovery, EarlyView.
Oscillatory Neural Networks (ONNs) are an emerging computing paradigm that encodes information in the phases of coupled oscillators. Traditionally, ONNs have been investigated using homogeneous frequency oscillators. However, physical hardware implementations are inherently subject to frequency mismatches, device variability, and nonuniformities.
Nil Dinç, Filip Sabo, Aida Todri‐Sanial   +2 more
wiley   +1 more source

Machine learning prediction of the mechanical properties of injection-molded polypropylene through X-ray diffraction analysis

Science and Technology of Advanced Materials
Predicting the mechanical properties of polymer materials using machine learning is essential for the design of next-generation of polymers. However, the strong relationship between the higher-order structure of polymers and their mechanical properties ...
Ryo Tamura, Kenji Nagata, Keitaro Sodeyama, Kensaku Nakamura, Toshiki Tokuhira, Satoshi Shibata, Kazuki Hammura, Hiroki Sugisawa, Masaya Kawamura, Teruki Tsurimoto, Masanobu Naito, Masahiko Demura, Takashi Nakanishi   +12 more
doaj   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Josephson parametric oscillator based Ising machine

Physical Review B
9 pages, 10 figures, 31 references.
Sasan Razmkhah, Mehdi Kamal, Nobuyuki Yoshikawa, Massoud Pedram   +3 more
openaire   +2 more sources

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Photonic Ising Machine Using Parallel Bandit Architecture Based on Laser Chaos

IEEE Access
Photonic computing has emerged as a transformative technology for overcoming the fundamental limitations of semiconductor technology. Among recent advancements, the laser chaos decision maker has been introduced for ultrafast decision making by ...
Ryota Yasudo, Michihiro Koibuchi, Mikio Hasegawa   +2 more
doaj   +1 more source

An Ising machine based on networks of subharmonic electrical resonators [PDF]

, 2022
L. Q. English, A. V. Zampetaki, K. P. Kalinin, Natalia G. Berloff, P. G. Kevrekidis   +4 more
openalex   +1 more source

A Multimodal Intelligent System for Human Digital Twin Simulation with Continuous Kinematic Data Tracking, Biometric Prognosis, and Cognitive State Feedback in Industrial Environments

Advanced Intelligent Discovery, EarlyView.
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury, Sebastian Gratz‐Kelly, Eric Wagner, Paul Motzki, Martina Lehser   +4 more
wiley   +1 more source

A 50-spin surface acoustic wave Ising machine

Communications Physics
Time-multiplexed spinwave Ising Machines have unveiled a route towards miniaturized and low-cost combinatorial optimization solvers but are constrained in the number of spins by nonlinear spinwave dispersion.
Artem Litvinenko, Roman Khymyn, Roman Ovcharov, Johan Åkerman   +3 more
doaj   +1 more source

Efficient and Scalable Architecture for Multiple-Chip Implementation of Simulated Bifurcation Machines

IEEE Access
Ising machines are specialized computers for finding the lowest energy states of Ising spin models, onto which many practical combinatorial optimization problems can be mapped. Simulated bifurcation (SB) is a quantum-inspired parallelizable algorithm for
Tomoya Kashimata, Masaya Yamasaki, Ryo Hidaka, Kosuke Tatsumura   +3 more
doaj   +1 more source